AI Technology on Dynamic Distributed IoT, Wireless, and Next-Generation Networking

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (30 September 2019) | Viewed by 3159

Special Issue Editor


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Guest Editor
Department of Computer Science, National Taichung University of Education, Taichung 40306, Taiwan
Interests: AI; machine learning; IoT; wireless; SDN; 5G networks; network slicing; dynamic distributed networks
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Special Issue Information

Dear Colleagues,

With the emerging technologies in Internet of Things (IoT), wireless, and next-generation networking, such as 5G networks, there is potential for acquiring and processing a tremendous amount of data from such dynamic distributed networks. On a technological level, the enormous amount of explosive data generated from IoT, wireless, and next-generation networks can be highly unstructured, heterogeneous, and unpredictable.

On the other hand, Artificial Intelligence (AI) has been extensively applied to domains in pattern or speech recognition, and related detection systems, such as outlier detection. However, the successful deployment for network operations, management, and applications on AI has been limited. This Special Issue is organized to discuss the state-of-the-art for the emerging technology, applications, and problems using AI, especially applications in the fields of dynamic distributed IoT, wireless, and next-generation networking issues.

This Special Issue solicits contributions from the field of IoT, wireless, and next-generation networking data analytics using AI technologies. Each submitted paper should cover solutions with the state-of-the-art and novel approaches for the related problems and challenges in AI perspectives. Topics to be discussed in this Special Issue include but are not limited to the following:

  • Artificial Intelligence (AI);
  • Innovative AI incentive schemes;
  • Distributed AI algorithms and techniques;
  • Machine learning;
  • Neural networks and applications;
  • Data mining;
  • Internet of Things (IoTs);
  • Wireless sensor and actuator networks (WSANs);
  • IPv6 over the time-slotted channel hopping mode of IEEE 802.15.4e (6TiSCH);
  • IoT system collaboration, cooperation mechanisms, and interoperability issues;
  • Security for IoT, WSN, SDN, and AI applications;
  • Advanced technology of IoT and applications;
  • Machine-2-machine (M2M) communications and interaction across application domains;
  • Software-defined networking (SDN) technology, system, and architecture;
  • QoS/QoE, performance evaluation, and integrated networks in SDN;
  • Next-generation networking technologies;
  • 5G networks and beyond technologies;
  • 5G networking applications and slice management;
  • Attacks and threads detection in 5G network slicing.

Prof. Dr. Lin-huang Chang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • AI
  • machine learning
  • IoT
  • wireless
  • SDN
  • 5G networks
  • network slicing
  • dynamic distributed networks

Published Papers (1 paper)

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Research

20 pages, 3468 KiB  
Article
Research on Cooperative Communication Strategy and Intelligent Agent Directional Source Grouping Algorithms for Internet of Things
by Yongyan Zou, Yanzhi Zhang and Xin Yi
Future Internet 2019, 11(11), 233; https://doi.org/10.3390/fi11110233 - 1 Nov 2019
Cited by 1 | Viewed by 2810
Abstract
In order to improve the network layer of the Internet of things to improve transmission reliability, save time delay and energy consumption, the Internet of things cooperative communication and intelligent agent technology were studied in this paper. In cooperative communication, a new cooperative [...] Read more.
In order to improve the network layer of the Internet of things to improve transmission reliability, save time delay and energy consumption, the Internet of things cooperative communication and intelligent agent technology were studied in this paper. In cooperative communication, a new cooperative communication algorithm KCN (k-cooperative node), and a reliability prediction model are proposed. The k value is determined by the end-to-end reliability. After k cooperative nodes are selected, other nodes enter dormancy. In aggregate traffic allocation, game theory is used to model the traffic equilibrium and end-to-end delay optimization scenarios. In practice, the optimal duty cycle can be calculated, which makes some cooperative nodes enter an idle state to save energy. Under the premise of guaranteeing end-to-end delay, it is shown that the reliability of the proposed KCN algorithm is better than that of the other existing routing protocols. In the aspect of intelligent agent, a Directional source grouping based multi-Agent Itinerary Planning (D-MIP) is proposed. This algorithm studies the routing problem of multi-agent parallel access to multiple source nodes. A directed source packet multi-agent routing planning algorithm is proposed. The iterative algorithm of each source node is limited to a sector, and the optimal intelligent agent route is obtained by selecting an appropriate angle. Compared with other algorithms, it is shown through a lot of simulated results that energy consumption and time delay has been saved by the proposed D-MIP algorithm. Full article
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